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Biomarkers of progression to multiple myeloma
AB
CD
Figure 3. Probability of progression to multiple myeloma from the time of the pre-diagnostic repeated blood sampling until latest follow-up. Immune marker levels are dichotomized according to receiver operating characteristic optimized cut-off values between individuals who progressed to multiple myeloma (n=58) and indi- viduals who did not (n=7). (A-D) Patients with low levels of an immune marker are represented in green, those with high levels in blue.
ary pattern of MM, decreasing measures of VEGF, FGF-2, fractalkine, and TGF-a might be indicative of disease pro- gression. The accuracy for predicting progression to MM was fair for pre-diagnostic repeated measures of TGF-a, with shorter time to progression in individuals having low levels of TGF-a (Figure 3). Thus, TGF-a measured in peripheral blood, could be of interest as a candidate bio- marker in the follow-up of patients with precursor condi- tions of MM.
The results of this study are consistent with previously published findings based on single samples per partici- pant.12 Nevertheless, it was unexpected that low blood levels of VEGF and FGF-2 closer to myeloma diagnosis might be associated with MM risk and progression as these growth factors are associated with tumor angiogen- esis.27 On the other hand, and more in line with our results, a recent study reported decreasing trends in plas- ma levels of soluble VEGFR-2 from MGUS to MM.11 Soluble VEGFR-2 is one of two soluble receptors of VEGF
Table 3. Multivariable Cox model for risk factors of progression.
Risk factor HRa
TGF-a, pg/mL
≥ 3.53 1.00 < 3.53 3.53
M-protein, g/L
<15 1.00 ≥15 1.58
M-protein type
IgG 1.00 Non-IgG 0.69
Immunoparesisb
No 1.00 Yes 1.20
FLC ratio
Normal 1.00 Abnormal 2.05
95%CI P
1.54 - 8.10
0.73 - 3.41
0.24 - 1.94
0.57 - 2.53
0.66 - 6.31
0.003
0.249
0.477
0.634
0.213
aHazard ratio (HR) association. bDepression of two uninvolved immunoglobulins.
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